I'm a Data Scientist with a Master's degree in Cognitive Science and a foundation in Philosophy. Understanding complex systems and building beneficial, practical, data-driven solutions is in my nature.
I’ve always had a curious mind, drawn to the big and interesting questions. My voyage started in philosophy. At the time, it seemed like the most reasonable path to embark on since that is where some of the most foundational questions are addressed. The abstract and verbal complexity of the subject was fascinating, but after some time, I realised I wanted to do more than what the philosophical method allowed for, I wanted to build.
Cognitive Science became the perfect bridge. It allowed me to take my passion for complex systems and apply it. My master's program was my proving ground, where I dove head-first into hands-on implementation: I designed EEG brain-computer interfaces, implemented AI into social robotics, and compared spatiotemporal data in VR and motion capture.
That hands-on experience was not only deeply rewarding, it solidified my path. Data Science was the clear next step, allowing me to specialize and focus my passion for complex systems on building concrete solutions. In collective work I’m known for being reliable and putting in the necessary effort, no matter how tough the task might seem, but I firmly believe that even the most serious work is done better with a calm, creative, and kind attitude. The series of steps I have taken has taught me that the goal is more than just building something technically sound; it's about applying a reflective process to create solutions that are thoughtful and valuable.
You might wonder how a background in philosophy fits with data science. For me, it’s not an add-on; it's the foundation. Before you brush off philosophy, here is what it taught me and how I apply it: